Comparison of Claims-Based Frailty Indices in U.S. Veterans 65 and Older for Prediction of Long-Term Institutionalization and Mortality

Abstract Background Frailty is increasingly recognized as a useful measure of vulnerability in older adults. Multiple claims-based frailty indices (CFIs) can readily identify individuals with frailty, but whether 1 CFI improves prediction over another is unknown. We sought to assess the ability of 5...

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Veröffentlicht in:The journals of gerontology. Series A, Biological sciences and medical sciences Biological sciences and medical sciences, 2023-10, Vol.78 (11), p.2136-2144
Hauptverfasser: Orkaby, Ariela R, Huan, Tianwen, Intrator, Orna, Cai, Shubing, Schwartz, Andrea W, Wieland, Darryl, Hall, Daniel E, Figueroa, Jose F, Strom, Jordan B, Kim, Dae H, Driver, Jane A, Kinosian, Bruce
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container_end_page 2144
container_issue 11
container_start_page 2136
container_title The journals of gerontology. Series A, Biological sciences and medical sciences
container_volume 78
creator Orkaby, Ariela R
Huan, Tianwen
Intrator, Orna
Cai, Shubing
Schwartz, Andrea W
Wieland, Darryl
Hall, Daniel E
Figueroa, Jose F
Strom, Jordan B
Kim, Dae H
Driver, Jane A
Kinosian, Bruce
description Abstract Background Frailty is increasingly recognized as a useful measure of vulnerability in older adults. Multiple claims-based frailty indices (CFIs) can readily identify individuals with frailty, but whether 1 CFI improves prediction over another is unknown. We sought to assess the ability of 5 distinct CFIs to predict long-term institutionalization (LTI) and mortality in older Veterans. Methods Retrospective study conducted in U.S. Veterans ≥65 years without prior LTI or hospice use in 2014. Five CFIs were compared: Kim, Orkaby (Veteran Affairs Frailty Index [VAFI]), Segal, Figueroa, and the JEN-FI, grounded in different theories of frailty: Rockwood cumulative deficit (Kim and VAFI), Fried physical phenotype (Segal), or expert opinion (Figueroa and JFI). The prevalence of frailty according to each CFI was compared. CFI performance for the coprimary outcomes of any LTI or mortality from 2015 to 2017 was examined. Because Segal and Kim include age, sex, or prior utilization, these variables were added to regression models to compare all 5 CFIs. Logistic regression was used to calculate model discrimination and calibration for both outcomes. Results A total of 3 million Veterans were included (mean age 75, 98% male participants, 80% White, and 9% Black). Frailty was identified for between 6.8% and 25.7% of the cohort with 2.6% identified as frail by all 5 CFIs. There was no meaningful difference between CFIs in the area under the receiver operating characteristic curve for LTI (0.78–0.80) or mortality (0.77–0.79). Conclusions Based on different frailty constructs, and identifying different subsets of the population, all 5 CFIs similarly predicted LTI or death, suggesting each could be used for prediction or analytics.
doi_str_mv 10.1093/gerona/glad157
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Multiple claims-based frailty indices (CFIs) can readily identify individuals with frailty, but whether 1 CFI improves prediction over another is unknown. We sought to assess the ability of 5 distinct CFIs to predict long-term institutionalization (LTI) and mortality in older Veterans. Methods Retrospective study conducted in U.S. Veterans ≥65 years without prior LTI or hospice use in 2014. Five CFIs were compared: Kim, Orkaby (Veteran Affairs Frailty Index [VAFI]), Segal, Figueroa, and the JEN-FI, grounded in different theories of frailty: Rockwood cumulative deficit (Kim and VAFI), Fried physical phenotype (Segal), or expert opinion (Figueroa and JFI). The prevalence of frailty according to each CFI was compared. CFI performance for the coprimary outcomes of any LTI or mortality from 2015 to 2017 was examined. Because Segal and Kim include age, sex, or prior utilization, these variables were added to regression models to compare all 5 CFIs. Logistic regression was used to calculate model discrimination and calibration for both outcomes. Results A total of 3 million Veterans were included (mean age 75, 98% male participants, 80% White, and 9% Black). Frailty was identified for between 6.8% and 25.7% of the cohort with 2.6% identified as frail by all 5 CFIs. There was no meaningful difference between CFIs in the area under the receiver operating characteristic curve for LTI (0.78–0.80) or mortality (0.77–0.79). Conclusions Based on different frailty constructs, and identifying different subsets of the population, all 5 CFIs similarly predicted LTI or death, suggesting each could be used for prediction or analytics.</description><identifier>ISSN: 1079-5006</identifier><identifier>ISSN: 1758-535X</identifier><identifier>EISSN: 1758-535X</identifier><identifier>DOI: 10.1093/gerona/glad157</identifier><identifier>PMID: 37395654</identifier><language>eng</language><publisher>US: Oxford University Press</publisher><subject>Aged ; Female ; Frail Elderly ; Frailty ; Frailty - epidemiology ; Geriatric Assessment ; Humans ; Institutionalization ; Male ; Mortality ; Phenotypes ; Predictions ; Regression analysis ; Retrospective Studies ; THE JOURNAL OF GERONTOLOGY: Medical Sciences ; Veterans ; Veterans health care</subject><ispartof>The journals of gerontology. 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Series A, Biological sciences and medical sciences</title><addtitle>J Gerontol A Biol Sci Med Sci</addtitle><description>Abstract Background Frailty is increasingly recognized as a useful measure of vulnerability in older adults. Multiple claims-based frailty indices (CFIs) can readily identify individuals with frailty, but whether 1 CFI improves prediction over another is unknown. We sought to assess the ability of 5 distinct CFIs to predict long-term institutionalization (LTI) and mortality in older Veterans. Methods Retrospective study conducted in U.S. Veterans ≥65 years without prior LTI or hospice use in 2014. Five CFIs were compared: Kim, Orkaby (Veteran Affairs Frailty Index [VAFI]), Segal, Figueroa, and the JEN-FI, grounded in different theories of frailty: Rockwood cumulative deficit (Kim and VAFI), Fried physical phenotype (Segal), or expert opinion (Figueroa and JFI). The prevalence of frailty according to each CFI was compared. CFI performance for the coprimary outcomes of any LTI or mortality from 2015 to 2017 was examined. Because Segal and Kim include age, sex, or prior utilization, these variables were added to regression models to compare all 5 CFIs. Logistic regression was used to calculate model discrimination and calibration for both outcomes. Results A total of 3 million Veterans were included (mean age 75, 98% male participants, 80% White, and 9% Black). Frailty was identified for between 6.8% and 25.7% of the cohort with 2.6% identified as frail by all 5 CFIs. There was no meaningful difference between CFIs in the area under the receiver operating characteristic curve for LTI (0.78–0.80) or mortality (0.77–0.79). 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Series A, Biological sciences and medical sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Orkaby, Ariela R</au><au>Huan, Tianwen</au><au>Intrator, Orna</au><au>Cai, Shubing</au><au>Schwartz, Andrea W</au><au>Wieland, Darryl</au><au>Hall, Daniel E</au><au>Figueroa, Jose F</au><au>Strom, Jordan B</au><au>Kim, Dae H</au><au>Driver, Jane A</au><au>Kinosian, Bruce</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of Claims-Based Frailty Indices in U.S. Veterans 65 and Older for Prediction of Long-Term Institutionalization and Mortality</atitle><jtitle>The journals of gerontology. Series A, Biological sciences and medical sciences</jtitle><addtitle>J Gerontol A Biol Sci Med Sci</addtitle><date>2023-10-28</date><risdate>2023</risdate><volume>78</volume><issue>11</issue><spage>2136</spage><epage>2144</epage><pages>2136-2144</pages><issn>1079-5006</issn><issn>1758-535X</issn><eissn>1758-535X</eissn><abstract>Abstract Background Frailty is increasingly recognized as a useful measure of vulnerability in older adults. Multiple claims-based frailty indices (CFIs) can readily identify individuals with frailty, but whether 1 CFI improves prediction over another is unknown. We sought to assess the ability of 5 distinct CFIs to predict long-term institutionalization (LTI) and mortality in older Veterans. Methods Retrospective study conducted in U.S. Veterans ≥65 years without prior LTI or hospice use in 2014. Five CFIs were compared: Kim, Orkaby (Veteran Affairs Frailty Index [VAFI]), Segal, Figueroa, and the JEN-FI, grounded in different theories of frailty: Rockwood cumulative deficit (Kim and VAFI), Fried physical phenotype (Segal), or expert opinion (Figueroa and JFI). The prevalence of frailty according to each CFI was compared. CFI performance for the coprimary outcomes of any LTI or mortality from 2015 to 2017 was examined. Because Segal and Kim include age, sex, or prior utilization, these variables were added to regression models to compare all 5 CFIs. Logistic regression was used to calculate model discrimination and calibration for both outcomes. Results A total of 3 million Veterans were included (mean age 75, 98% male participants, 80% White, and 9% Black). Frailty was identified for between 6.8% and 25.7% of the cohort with 2.6% identified as frail by all 5 CFIs. There was no meaningful difference between CFIs in the area under the receiver operating characteristic curve for LTI (0.78–0.80) or mortality (0.77–0.79). Conclusions Based on different frailty constructs, and identifying different subsets of the population, all 5 CFIs similarly predicted LTI or death, suggesting each could be used for prediction or analytics.</abstract><cop>US</cop><pub>Oxford University Press</pub><pmid>37395654</pmid><doi>10.1093/gerona/glad157</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-6592-6141</orcidid><orcidid>https://orcid.org/0000-0001-9759-4607</orcidid><orcidid>https://orcid.org/0000-0001-7290-6838</orcidid><orcidid>https://orcid.org/0000-0002-4297-6306</orcidid><orcidid>https://orcid.org/0000-0003-2098-6340</orcidid><oa>free_for_read</oa></addata></record>
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subjects Aged
Female
Frail Elderly
Frailty
Frailty - epidemiology
Geriatric Assessment
Humans
Institutionalization
Male
Mortality
Phenotypes
Predictions
Regression analysis
Retrospective Studies
THE JOURNAL OF GERONTOLOGY: Medical Sciences
Veterans
Veterans health care
title Comparison of Claims-Based Frailty Indices in U.S. Veterans 65 and Older for Prediction of Long-Term Institutionalization and Mortality
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